Proper document structure improves readability for both humans and AI (GPT models from OpenAI read markdown best, while anthropic models read XML). We recommend using a clear hierarchy with headings, subheadings, and bullet points.

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# Product X User Manual 

## 1. Introduction 
- Overview of Product X 
- Key features and benefits 

## 2. Getting Started 
- Unboxing and setup 
- Initial configuration 

## 3. Basic Operations 
- Powering on/off 
- Navigating the user interface 

## 4. Advanced Features 
- Custom settings 
- Integration with other devices 

## 5. Troubleshooting 
- Common issues and solutions 
- Contacting support

Consistent structure across documents helps the AI agent quickly locate and extract relevant information, leading to more accurate and context-aware responses. To quickly reformat documents, feed the text to an LLM.

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Adding Descriptions and Tags

Each of the text ingestion methods explained above all include the following fields to enhance your knowledge base’s searchability and efficiency:

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Document Description

Write a brief (2-3 sentences) summary of the document’s content. For example:


  "This document outlines our company's customer return policy, including eligibility criteria, timeframes, and refund processes."

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Tags

Tags Add relevant keywords that describe the document’s main topics. For instance:


  customer-service, returns, refunds, policy

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These descriptions and tags help the LLM understand the context and relevance of each document, improving the accuracy of information retrieval. We recommend doing both for best possible retrieval and output.

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